This section presents the context for describing interventions to change physical activity behavior in terms of characteristics of the person (i.e., the target group), the setting, and the level of the intervention. Characteristics of the target group, such as age, living situation, and income, should be considered in selecting interventions. For example, a program for increasing physical activity in overweight middle school children will be very different from a program to increase the number of factory workers who adopt regular exercise. The setting, which can range from a high school physical education class to an urban recreation facility, presents a variety of resources and limitations. Interventions can be applied on an individual, group, community, or societal level, and this will also influence the choice of strategies. Numerous approaches have been used to influence physical activity. This chapter provides descriptions of several interventions applied to various populations and their potential for changing physical activity behavior. We end with a discussion of issues involved in the development and implementation of exercise behavior change interventions.
Characteristics of the Person
It is becoming increasingly evident that interventions applied in general, without consideration of the unique demands of the population, have limited impact. One size does not fit all. Information about the client or target group enables us to select the best strategy, the most appropriate setting in which to implement the strategy, and the level of intervention that will have the greatest impact. Exercise stage, demographic characteristics, cognitive variables (e.g., knowledge, attitudes, and beliefs), and self-regulation skills (e.g., goal setting, self-monitoring) are some of the personal characteristics that have been considered in the development and implementation of exercise interventions.
Exercise Stage of Change
Determining exercise stage of change as described by the transtheoretical model of behavior change (TTM; see chapter 14) is useful because different goals and strategies are necessary based on whether the person is currently active and the person’s intentions to begin or maintain regular exercise (see table 15.1). Although there is some evidence that current stage based on the TTM is not useful for predicting changes in physical activity (Dishman, Thom, et al. 2009), a person’s current and past levels of physical activity and motivational readiness (behavioral intention) can be useful in selecting goals and strategies. For example, the health action process approach (HAPA; Schwarzer et al. 2007; Schwarzer et al. 2008) distinguishes among nonintentional, intentional, and action stages and recommends corresponding strategies. Motivational interventions are applied to someone in the nonintentional stage, and action planning (e.g., specifying when, where, and how the activity will be performed and overcoming anticipated barriers to action) is applied to someone in the intentional or action stage. Stage-matched strategies based on HAPA were tested in an Internet-based intervention by Lippke and colleagues (2010), in which significantly more members of the group receiving the stage-based intervention moved forward to the action stage than did those in the control condition.
Traditional strategies will not work with someone who is not ready to change. For example, people in the precontemplation,or nonintentional, stage may be resistant to recognizing or modifying a problem. Auweele, Rzewnicki, and Van Mele (1997) examined factors in the adoption of exercise in 133 male and 132 female sedentary middle-aged adults in Belgium. They found a significant group of indifferent sedentary adults for whom exercise was irrelevant (60% of the total sample). These people did not include exercise as part of their lives or self-concepts and did not see exercise as a way to achieve desired goals. The authors proposed that some people may simply not be receptive to any intervention.
The stages of the TTM have often been used to categorize participants before selecting intervention strategies. Contemplators are aware of the problem and are thinking about changing, but they have not made the commitment to change. At this point, the costs of exercising are perceived to be greater than the benefits. Cognitive factors to consider are the perceived barriers to starting an exercise program, outcome expectations, outcome values, and psychosocial variables, such as exercise self-efficacy. Exercise history can affect self-efficacy in that those who have had positive experiences with exercise will have more confidence in their ability to exercise again.
People in the preparation stage have already begun to change their behavior. They intend to begin regular exercise within a short period of time and may already be exercising, but below a criterion level. Setting goals that are based on capabilities, values, resources, and needs is important. Accomplishing challenging goals will increase a sense of mastery, which will also enhance exercise self-efficacy.
Most people who start an exercise program drop out within the first six months. Therefore, the first few months after someone has adopted regular exercise (the action stage)are critical. Establishing a regular exercise routine involves a significant commitment of time and energy. According to habit theory (chapter 14), most of the behaviors necessary for engaging in exercise still require conscious consideration and active decision making in the early adoption period. Action planning is critical in early adoption according to HAPA. Other strategies such as those in table 15.1 can support the new behavioral patterns while exercise becomes a more established, automatic routine.
Maintaining regular exercise is the goal for novice and long-term exercisers. People who have been regularly active for more than six months (maintenance stage) have a decreased risk of relapse. However, permanent maintenance is not guaranteed, and there remains the potential for lapses in an exercise routine as a result of relocation, family commitments, travel, medical events, or other disruptions. The physical activity maintenance model (PAM; see chapter 14) examines the individual psychological and contextual variables that support or impede long-term maintenance. For example, because PAM identifies stress as a potential trigger of relapse, stress management would be one technique for promoting exercise maintenance.
Demographic variables, such as age, sex, ethnicity, and education, are not targets for change. However, demographic variables often function as moderators. As noted in chapter 2, a moderator is a variable that affects the direction or strength (or both) of the relationship between the independent variable and the outcome variable. Moderators always function as independent variables (Baron and Kenny 1986) and can be represented by an interaction, such as better adherence for men than women to an exercise intervention that promotes competition (see figure 15.1).
Demographic characteristics can influence the receptiveness to interventions and the exercise behavior itself. Obviously, the presentation of the intervention and the materials must suit the educational level and developmental stage of the target group. Behavior change strategies and physical activities that will appeal to elementary school children are not the same as those that will motivate college students. Demographic characteristics also yield important information about structuring an intervention so that it is more enticing to participants. For example, older adults as compared to younger people find health and fitness motives more salient for adopting and maintaining an active lifestyle. Women are more likely than men to adopt exercise for weight loss (e.g., McAuley et al. 1994), but this may not be the case with African-American women (see chapter 12). Appearance and social interaction may also be more important in an exercise program for women than for men, who may find competitiveness a greater incentive to exercise (Markland and Hardy 1993). Interventions that have been effective with minority populations have tailored strategies to be sensitive to cultural beliefs, values, language, literacy, and customs (Artinian et al. 2010).
Identifying attitudes and beliefs about physical activity provides important information for designing and implementing behavior change strategies. For example, we would not expect a sedentary middle-aged woman who believes she is active enough in her job to respond to a sign-up sheet for a work site aerobics program, but she may be ready to listen to compelling information in a media campaign about the benefits of physical activity for women like herself. Knowledge is not enough to change behavior, but clear, relevant information about the personal benefits of physical activity and practical suggestions for ways to become more active can influence attitudes, beliefs, and expectations.
Exercise self-efficacy is frequently studied as a correlate of exercise behavior and is a key mediator of behavior change according to several theoretical models. The relationship between self-efficacy and exercise adoption is fairly consistent, but the role of self-efficacy in maintenance depends on the type of self-efficacy. Oman and King (1998) and McAuley, Courneya, and colleagues (1994) examined the relationship between self-efficacy and exercise and found good evidence for effects of self-efficacy on adoption but not on adherence. However, Garcia and King (1991) examined the relationship between self-efficacy and exercise adherence in a middle-aged community sample and found a positive correlation between self-efficacy and adherence for months 1 to 6 and months 7 to 12.